A Machine Learning Approach to Fault Prediction of Power Distribution Grids under Heatwaves-Reference-Cited by-同舟云学术

A Machine Learning Approach to Fault Prediction of Power Distribution Grids under Heatwaves

Published:2023 Issue: Volume: Page:1-11
ISSN:0093-9994
Container-title:IEEE Transactions on Industry Applications
language:
Short-container-title:IEEE Trans. on Ind. Applicat.

Author:

Atrigna Mauro¹^ORCID,Buonanno Amedeo¹^ORCID,Carli Raffaele²^ORCID,Cavone Graziana³,Scarabaggio Paolo²^ORCID,Valenti Maria¹,Graditi Giorgio⁴^ORCID,Dotoli Mariagrazia²^ORCID

Affiliation:

1. Department of Energy Technologies and Renewable Energy Sources - Smart Grid and Energy Networks Lab (TERIN-STSN-SGRE) of ENEA, Centre of Portici (Neaples), Italy

2. Department of Electrical and Information Engineering, The Polytechnic of Bari, Italy

3. Department of Engineering, University Roma Tre, Rome, Italy

4. Department of Energy Technologies and Renewable Energy Sources (TERIN) of ENEA, Centre of Casaccia (Rome), Italy

Funder

Italian University and Research Ministry

RAFAEL (National Research Program

Research for Innovation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Industrial and Manufacturing Engineering,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/28/4957013/10081504.pdf?arnumber=10081504

Reference48 articles.

1. Analyzing the Impact of Failures in the Electric Power Distribution Grid

2. Failure rates reduction in SmartGrid MV underground distribution cables: Influence of temperature

3. Failures of medium voltage cable joints in relation to the ambient temperature

4. Power System State Estimation

5. Joints defectiveness of MV underground cable and the effects on the distribution system

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